Open AccessDiversiNews: Surfacing Diversity in Online News
Author(s) -
Trampuš Mitja,
Fuart Flavio,
Pighin Daniele,
Štajner Tadej,
Bercic Jan,
Novak Blaž,
Rusu Delia,
Stopar Luka,
Grobelnik Marko
Publication year - 2015
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v36i4.2528
Subject(s) - ranking (information retrieval) , geolocation , event (particle physics) , aggregate (composite) , computer science , news aggregator , information retrieval , set (abstract data type) , perspective (graphical) , feature (linguistics) , learning to rank , diversity (politics) , contrast (vision) , data science , world wide web , artificial intelligence , linguistics , philosophy , physics , materials science , quantum mechanics , sociology , anthropology , composite material , programming language
For most events of at least moderate significance, there are likely tens, often hundreds or thousands of online articles reporting on it, each from a slightly different perspective. If we want to understand an event in depth, from multiple perspectives, we need to aggregate multiple sources and understand the relations between them. However, current news aggregators do not offer this kind of functionality. As a step toward a solution, we propose DiversiNews, a real‐time news aggregation and exploration platfom whose main feature is a novel set of controls that allow users to contrast reports of a selected event based on topical emphases, sentiment differences, and/or publisher geolocation. News events are presented in the form of a ranked list of articles pertaining to the event and an automatically generated summary. Both the ranking and the summary are interactive and respond in real time to user's change of controls. We validated the concept and the user interface through user tests with positive results.